In this second revision of our competitive renewal application, we propose to continue our work to enhance diagnostic accuracy in late-life mental illness. In addition, we propose new initiatives to identify physiologic indicators of prognosis in dementia and depression, and to develop physiologic predictors of antidepressant treatment response. The hypotheses are designed to address problems of clinical importance, and are based upon significant pilot data. In response to the Committee's critique, we have made significant revisions to this application. We have: 1) made our hypotheses more specific regarding the diagnosis and treatment of depression; 2) increased the number of subjects in the depressed group from 100 of 180; 3) eliminated ECT as a possible treatment; 4) revised our data analysis procedures to control for possible confounding variables, including baseline levels of function; 5) added more detail regarding mechanisms underlying our hypotheses; and 6) included new pilot data that support our hypotheses, and the clinical applications of our techniques. This proposal aims to: first, complete validation of QEEG as a method for the differential diagnosis of dementia and depression; second, use QEEG methods to identify indicators of prognosis in dementia and depression; third, develop neurophysiologic predictors of antidepressant treatment response; and, fourth, examine the functional significance of white- matter lesions with integrated MRI/QEEG, and assess the role of lesions in development of mental illness. We will test four hypotheses: 1) QEEG cordance and coherence are sensitive and specific measures for the diagnosis of dementia of the Alzheimer's type (DAT), multi-infarct dementia (MID), mixed DAT/MID dementia (MIX), and depression (DEP); 2) Low coherence at baseline will be associated with increased psychiatric symptoms and decreased functional status at follow-up in patients with dementia or DEP; 3) Changes in cordance during the course of antidepressant treatment will predict response to medication; and, 4) A combination of coherence and MRI lesion volume will identify those patients and normal controls (CON) at increased risk for recurrent depression, and cognitive and/or functional decline. We will accomplish these aims through a four-step plan. First, we will continue follow-up of our existing cohort of DAT, MID, and CON subjects, focusing on the evolution of functional disability and behavioral symptoms in relation to QEEG variables, and upon autopsy validation of clinical and QEEG- based diagnoses. Second, we will recruit new subjects with mild dementia or DEP, to prospectively examine the sensitivity and specificity of QEEG for diagnosis of these illnesses, and to identify QEEG predictors of treatment outcome and long-term prognosis. Third, we will intensively examine DEP subjects during the course of treatment to identify predictors of antidepressant response. Fourth, we will perform three-dimensional analysis of serial QEEG/MRI studies in DEP and CON subjects to identify the type and/or location of white-matter disease associated with altered brain function. Serial study will determine characteristics of lesions that adversely affect long-term prognosis, as well as the usefulness of QEEG for monitoring the evolution of white-matter disease.